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Social Networks such as Facebook, Twitter, Google+
and LinkedIn have millions of users. These networks are constantly
evolving and it is a good source of information, both
explicitly and implicitly. The analysis of Social Network mainly
focuses on the aspect of social networking with an emphasis
on mapping relationships, patterns of interaction between user
and content information. One of the common research topics
focuses on the centrality measures where useful information of
the connected people in the social network is represented in
a graph. In this paper, we employed two link-based ranking
algorithms to analyze the ranking of the users: HITS (Hyperlink-
Induced Topic Search) and PageRank. We constructed Twitter
user retweet-relationship graph using 21 days worth of data.
Lastly, we compared the ranking sequence of the users in addition
to their followers count against the average and also whether
they are verified Twitter accounts. From the results obtained,
both HITS and PageRank showed a similar trend, and more
importantly highlighted the importance of the direction of the
edges in this work.

17.
Results
Closer look of how TeamMsia involved in the conversation.
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18.
Summary
 The use of Link-based ranking algorithms such
as Page Rank and HITS does promise us some
insights about concerningTwitter Users and
their significance.
 These insights can be useful for Customer Care
/ Churn Management
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